Preliminary experiments on discriminating between chaotic signals and noise using evolutionary programming

Authors:
David B. Fogel;Lawrence J. Fogel
Affiliations:
Natural Selection, Inc., La Jolla, CA;Natural Selection, Inc., La Jolla, CA
Venue:
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
Year:
1996

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Abstract

Evolutionary programming is a stochastic optimization algorithm that can be used for system identification. This paper focuses on the use of evolutionary programming for optimizing models of chaotic signals, both with and without additive noise. Preliminary results indicate that the method may be useful for estimating parameters of nonlinear chaotic sequences and can assist in detecting the presence or absence of a chaotic signal in an observed time series.